Tuning of length-scale and observation-error for radar data assimilation using four dimensional variational (4D-Var) method

The effects of tuning of length-scale and observation-error on heavy rainfall forecasts are investigated. Length scale and observation error are tuned based on observation minus background (O - B) covariances and theoretically expected cost function values, respectively. Tuned length scale and observation error are applied to radar data assimilation using the Four Dimensional Variational (4D-Var) method. Length-scale tuning leads to improved Quantitative Precipitation Forecast (QPF) skill for heavy precipitation, better analyses, and reduced errors of wind, temperature, humidity, and hydrometeor forecasts. The effects of observation-error tuning are not as significant as those of length-scale tuning, and they are limited to improvements in QPF skill. This is because tuned observation errors are close to pre-assumed values. Proper tuning of length-scale and observation-error is essential for radar data assimilation using the 4D-Var method.

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Author Choi, Yonghan
Cha, D.
Kim, J.
Publisher UCAR/NCAR - Library
Publication Date 2017-11-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2025-07-11T19:44:40.154172
Metadata Record Identifier edu.ucar.opensky::articles:21185
Metadata Language eng; USA
Suggested Citation Choi, Yonghan, Cha, D., Kim, J.. (2017). Tuning of length-scale and observation-error for radar data assimilation using four dimensional variational (4D-Var) method. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d7jd50dh. Accessed 07 August 2025.

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